Trends in Soil Science over the Past Three Decades (1992–2022) Based on the Scientometric Analysis of 39 Soil Science Journals
Bibliographic record
Abstract
As one of the basic disciplines of agricultural, natural resource, and environmental science, soil science has played a critical role in global food security and socio-economic and ecological sustainability. The number of soil science journals and publications has increased remarkably with the development of soil science. However, there is a lack of systematic and comprehensive studies on the developmental trends of soil science based on journals and publications. In this study, 39 journals included under the soil science category in the 2022 Journal Citation Reports, and 112,911 publications in these journals from 1992 to 2022 were subjected to scientometric/bibliometric analysis to determine trends in publication, journal metrics, co-authorship, and research topics, in addition to general journal information. The results show that soil science ushered in a renaissance period with the number of publications, citations, impact factors, and CiteScore demonstrating an increasing trend. America and the Chinese Academy of Sciences had the most publications and citations. The most productive author published more than 400 articles. Soil science research focused mostly on its fundamental impact on the ecological environment based on the strongest citation bursts analysis of keywords. The analysis indicated that open access has increased in popularity. Current soil science journals still face a few common challenges, including an urgent need for a fairer evaluation mechanism on journal quality compared to the traditional use of single metrics as well as equity, diversity, and inclusion (EDI) in the whole editorial process. Artificial intelligence may bring new tools and more changes to the development of soil science. This study will help soil science researchers to better understand the development status and future trends of soil science. It will also guide authors in journal selection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.087 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".